Mandibular Symphyseal Height Determination in Various Vertical Patterns
Bibliographic record
Abstract
The mandibular symphysis is a crucial anatomical structure influencing facial aesthetics and harmony. Its morphology is pivotal in determining optimal lower incisor positioning, especially in borderline orthodontic cases requiring meticulous treatment planning. Objective: To determine and compare symphyseal dimensions in different vertical patterns of skeletal class I cases. Methods: The study was designed as a cross-sectional study. Data was analyzed using SPSS 25, with mean and standard deviations used for quantitative variables and frequency and proportions for qualitative data. Statistical significance was assessed using chi-square tests for gender and ANOVA for symphysis height and vertical facial patterns, with a P-value ≤0.05 considered significant. Results: Male subjects with Hypodivergent (↓D), Normodivergent (ND)and Hyperdivergent (↑D) profiles showed no statistically significant difference in Id-Me, whereas female subjects showed statistically significant difference in Id-Me between (↓D) and (↑D) subjects. Additionally, a notable sex difference was observed in Id-Me, with significant variations between males and females. In contrast, the differences in LI between males and females were found to be statistically non-significant (P > 0.05). Conclusion: This article reflected that males show longer chin than females.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".